Principle Data Scientist; III​/IV​/V – Sensor Analytics & Data Fusion

Company Overview

WGS Systems, a leading innovator in communications and defense industries, is looking to expand our leveraging of advanced data solutions for mission-critical applications. We seek an experienced professional to join our dynamic team in building scalable AI systems from raw, high-volume data sources. This role offers opportunities to impact real-world projects in a collaborative, high-tech environment.

We are seeking a (Principle) Data Scientist to drive the development of a novel intelligence platform that fuses proprietary sensor data with high-volume commercial datasets to deliver actionable recommendations to our customers. This role sits at the intersection of sensor development, multi-source data integration, and AI-driven decision support.

You will define what signals our sensors should capture, evaluate and integrate commercial data sources, architect scalable analytics infrastructure, and build machine learning models that transform raw data into customer-ready intelligence products. As we scale, you’ll help grow and mentor our data science team while partnering closely with sensor and software engineering teams.

This is a high-impact, product-focused role requiring both hands-on technical expertise and strategic thinking about data-driven product development.

• Product & Strategy:
  • Partner with CTO and engineering leadership to define sensor collection priorities based on commercial data availability and customer intelligence gaps
  • Evaluate, pilot, and recommend commercial data sources for integration (e.g., satellite imagery, AIS/ADS-B, signals databases, geospatial intelligence)
  • Architect end-to-end data pipelines and analytics infrastructure to support multi-source fusion at scale
  • Define data science roadmap aligned with product development milestones and customer needs
• Sensor Data Co-Development
  • Analyze commercial and operational data to identify high-value signals and features for proprietary sensor collection
  • Develop algorithms that optimize sensor performance and collection strategies through data-driven feedback
  • Design experiments to validate sensor utility and correlation with existing intelligence sources
• Model Development & Data Fusion
  • Build ML models that fuse proprietary sensor data with commercial datasets to detect patterns, anomalies, and emerging trends
  • Develop recommendation engines and decision support algorithms that deliver actionable products to customers
  • Implement explainable AI techniques to ensure model transparency for stakeholders
• Technical Leadership & Collaboration
  • Provide technical mentorship to growing data science team; establish best practices for model development, testing, and deployment
  • Collaborate with sensor hardware and software engineering teams to ensure data collection, storage, and processing requirements are met
  • Deploy production ML systems using cloud infrastructure (AWS/GCP) with appropriate security controls
  • Communicate technical findings and data-driven insights to customers and non-technical stakeholders

• Master’s or PhD in Computer Science, Statistics, Electrical Engineering, Data Science, or related quantitative field
• We encourage applicants at different stages of their career to apply, and will hire at the level that fits the successful applicants background.
  • Data Scientist III: 4+ years in data science/ML engineering with at least 2+ years working with sensor data, signals intelligence, or multi-source data fusion
  • Data Scientist IV: 6+ years in data science/ML engineering with at least 2+ years working with sensor data, signals intelligence, or multi-source data fusion
  • Principal Data Scientist: 8+ years in data science/ML engineering with at least 2+ years working with sensor data, signals intelligence, or multi-source data fusion
• S. Citizen with active Secret clearance or ability to obtain TS/SCI (adjust based on your program requirements)
• Expert Python programming; production ML experience with tools like Tensor Flow/PyTorch/Scikit-learn
• Demonstrated experience evaluating, acquiring, and integrating third-party datasets into analytics pipelines
• Strong foundation in signal processing, feature engineering, and time-series analysis
• Experience deploying production ML systems on cloud platforms with MLOps practices
• Track record of translating ambiguous problems into technical solutions with measurable customer impact
• Excellent communication skills with demonstrated experience working across hardware, software, and business stakeholders

• Background in defense, intelligence community, or aerospace with knowledge of SIGINT, GEOINT, or ISR operations
• Experience with sensor phenomenology (RF, EO/IR, acoustic, etc.) and understanding of sensor performance parameters
• Familiarity with commercial intelligence data sources: satellite imagery providers (Maxar, Planet), AIS/ADS-B, open-source intelligence (OSINT) platforms
• Experience with geospatial analytics, temporal pattern detection, or maritime/aviation…